Resource Scheduling Optimization under Multi-Access Edge Computing Architecture
Lixia Bao, Yue Yang, Jiaqing Mao, Zhibo Gao, Zhizhou Wu · CICTP 2022 · 2022
We constructed a vehicular network architecture combining multi-access edge computing (MEC) to address the serious problem of delay and energy consumption increase and service quality degradation caused by complex network status and huge amounts of computing data in the scenario of vehicle-to-everything (V2X). MEC services the edge of the wireless network to compensate for the delay fluctuation caused by remote cloud computing. We derived the optimal offloading decision, communication, and computing resource allocation scheme by modeling the MEC-based V2X offloading and resource allocation in a typical four-leg unsignalized intersection. The waste of communication resources caused by the uneven distribution of vehicles on each entrance is obviously reduced. An experiment is conducted, and the results showed that, as compared to other mechanisms, the proposed mechanism can utilize MEC resources and effectively reduce system cost.